Ejemplo n.º 1
0
 def get_config(self):
     config = {
         k: backend.eval(v) if tf_utils.is_tensor_or_variable(v) else v
         for k, v in self._fn_kwargs.items()
     }
     base_config = super().get_config()
     return dict(list(base_config.items()) + list(config.items()))
Ejemplo n.º 2
0
    def get_config(self):
        config = {}

        if type(self) is MeanMetricWrapper:  # pylint: disable=unidiomatic-typecheck
            # Only include function argument when the object is a MeanMetricWrapper
            # and not a subclass.
            config['fn'] = self._fn

        for k, v in self._fn_kwargs.items():
            config[k] = backend.eval(v) if is_tensor_or_variable(v) else v
        base_config = super().get_config()
        return dict(list(base_config.items()) + list(config.items()))
Ejemplo n.º 3
0
    def get_config(self):
        config = {
            k: backend.eval(v) if tf_utils.is_tensor_or_variable(v) else v
            for k, v in self._fn_kwargs.items()
        }

        if type(self) is MeanMetricWrapper:
            # Only include function argument when the object is a
            # MeanMetricWrapper and not a subclass.
            config["fn"] = self._fn

        base_config = super().get_config()
        return dict(list(base_config.items()) + list(config.items()))
Ejemplo n.º 4
0
 def get_config(self):
     config = {}
     for k, v in self._fn_kwargs.items():
         config[k] = backend.eval(v) if is_tensor_or_variable(v) else v
     base_config = super().get_config()
     return dict(list(base_config.items()) + list(config.items()))